The mining sector faces challenges as legacy technologies fail to keep up with the growing demand for advanced mining activities for increased outputs and greater profits. Against this backdrop, artificial intelligence (AI) can help make mining companies more productive and profitable with insights-led decisions across the value chain, says GlobalData, a leading data and analytics company.
Abhishek Paul Choudhury, Senior Disruptive Tech Analyst at GlobalData, comments: “Mining leaders must adopt AI and its relevant technologies like machine learning (ML) and deep learning (DL) to turn challenges into opportunities with data-driven insights that can help them with several aspects of mining activities ranging from ore exploration to extraction, and mineral processing to marketing.”
GlobalData’s latest Innovation Radar report, “Digital mine: how technology is transforming mining from prospecting to reclamation Vol.2,” highlights how AI-related solutions are improving processes across the mining sector value chain.
Australia’s Datarock introduced Datarock Core (Core) platform that leverages DL to automate the extraction of geological information from imagery and videos. The platform allows users to upload imagery and apply various general or custom deep learning models to analyze the data for quality assurance (QA) and quality check (QC) purposes and extract various important types of geological and geotechnical information.
German chemical company BASF partnered with British AI startup IntelliSense.io to develop ‘BASF Intelligent Mine’ solution to help mining companies in making their operations safe, efficient, and sustainable. With both on-site and cloud deployment features, it offers Optimization-as-a-Service (OaaS) to help mine operators predict and simulate the future performance of a mining site and obtain process-specific recommendations.
Australian mining equipment provider MineWare has rolled out an AI-powered drill automation platform named Phoenix AI that helps mining companies with the optimization of blast-hole drill operations. This can reduce poor hole quality and machine stress to eliminate the need to tune operational parameters on the machine with continuous monitoring and action-oriented insights.
Commodity Price Prediction
American technology startup Akkio introduced a forecasting solution for the mining sector to help forecast commodity prices and plan business accordingly. It uses AI/ML to access historic data on commodity prices and sales volume to simplify forecasting mineral commodities with models that can be deployed via an application programming interface (API), Zapier, Salesforce, or a web app.
Choudhury concludes: “AI and related applications can bring tangible benefits and are already showing improvements in mining business outcomes. It is safe to comment that there will be more AI-based developments to catalyze data-augmented optimal business decisions for the mining sector.”